Abstract
Abstract This paper solves the dynamic portfolio allocation problem with account of time-varying jump risk. We find that both the initial jump intensity as a state variable and the jump dynamics including the average jump intensity and jump persistence are important for the investor’s optimal portfolio decision. The risk-averse investor can benefit from the optimal dynamic strategy instead of the myopic strategy. The out-of-sample results show that compared with the no-jump model, constant-jump model or the equal weighted portfolio, the dynamic portfolio with account of time-varying jump risk can produce better performance, and is more preferred by the risk-averse investor.
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